JuliaGraphs / JuliaGraphs/GraphNeuralNetworks.jl
Support for GNN specific Normalisation Layers
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 308
- Forks
- 74
- Avg merge
- 3d 6h
- Merged PRs (30d)
- 2
Description
There are GNN specific normalisations which play a crucial role in Deeper GNNs, or help in overcoming oversmoothing.
There arises a necessity to implement these in order to enhance the Deeper GNNs .
Listing a few important GNN normalisation functionalities / layers here . Will be constantly updating it
- PairNorm
- GraphNorm
I will be working on the implementation of these and will make a PR on it and add more useful normalisations here
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names PairNorm and GraphNorm but gives no files, tests, or entry points. First confirm whether the proposed implementation is still available, then review the project's existing GNN layer conventions and define tests for both normalisations. Done means both checklist items are implemented and covered by tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100